NFL Rostergen: R-Shiny Application for Optimizing NFL Team Construction Using Genetic Algorithms

10 Pages Posted: 12 Jul 2022

See all articles by Sumedh Khodke

Sumedh Khodke

State University of New York (SUNY) - Buffalo

Evan Fox

State University of New York (SUNY) - Buffalo

Dineshkumar Katta

State University of New York (SUNY) - Buffalo

Amritha Subburayan

State University of New York (SUNY) - Buffalo

Sanjay Aravind Loganathan Ravichandran

State University of New York (SUNY) - Buffalo

Nazmus Sakib

Kennesaw State University - Department of Information Systems

Abstract

Roster construction is critical in any sport for the team's subsequent performance. The significance of this project is to create better team construction strategies for American Football teams in the NFL, and the solution can be extrapolated to other sports. Multiple factors influence the selection process, such as current team construction, player skill, financial constraints, which may complicate the process of selecting 53-man rosters since there are several permutations for a greedy-search heuristic. The goal of this project is to use a Genetic Algorithm to objectively select players by integrating an ML-based fitness function used to evaluate a team’s quality.

Keywords: NFL, Roster-formulation, Genetic-Algorithm, Fitness-Function

Suggested Citation

Khodke, Sumedh and Fox, Evan and Katta, Dineshkumar and Subburayan, Amritha and Ravichandran, Sanjay Aravind Loganathan and Sakib, Nazmus, NFL Rostergen: R-Shiny Application for Optimizing NFL Team Construction Using Genetic Algorithms. Available at SSRN: https://ssrn.com/abstract=4160518 or http://dx.doi.org/10.2139/ssrn.4160518

Sumedh Khodke

State University of New York (SUNY) - Buffalo ( email )

Evan Fox

State University of New York (SUNY) - Buffalo ( email )

Dineshkumar Katta

State University of New York (SUNY) - Buffalo ( email )

Amritha Subburayan

State University of New York (SUNY) - Buffalo ( email )

Sanjay Aravind Loganathan Ravichandran

State University of New York (SUNY) - Buffalo ( email )

Nazmus Sakib (Contact Author)

Kennesaw State University - Department of Information Systems ( email )

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